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CSDA
2007
108views more  CSDA 2007»
13 years 10 months ago
Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio
INFOCOM
2009
IEEE
14 years 4 months ago
Robust Event Boundary Detection in Sensor Networks - A Mixture Model Based Approach
—Detecting event frontline or boundary sensors in a complex sensor network environment is one of the critical problems for sensor network applications. In this paper, we propose ...
Min Ding, Xiuzhen Cheng
WSC
2004
13 years 11 months ago
Global Likelihood Optimization Via the Cross-Entropy Method, with an Application to Mixture Models
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
Zdravko I. Botev, Dirk P. Kroese
ICIP
2006
IEEE
14 years 11 months ago
Video Event Detection using ICA Mixture Hidden Markov Models
In this paper, a framework that combines feature extraction, model learning, and likelihood computation, is presented for video event detection. First, the independent component a...
Jian Zhou, Xiao-Ping Zhang
ICML
2003
IEEE
14 years 10 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...